This thesis focuses on the development and assessment of the energy model for the Unterhaching district using EUReCA and UrbanHeatPro. These models have been respectively developed by the Department of Industrial Engineering at the University of Padua and by the Chair of Renewable and Sustainable Energy Systems at the Technical University of Munich (TUM). The main purpose is to analyse the differences between the two software tools and how they provide heating and cooling energy demands by simulating the behavior of an entire city, specifically Unterhaching. Consequently, two main simulations will be presented: the first simulation considers consumption using real input data from UrbanHeatPro and EUReCA as set by their respective universities (this simulation will be referred to as "simulation with no adaptation of input data"); the second simulation ("simulation with adaptation of input data") involves making the input data between the two software tools as similar as possible in order to understand whether the differences between the models stem from input data or the different models used. Subsequently, another section will be addressed where optimization will be discussed. This involves evaluating two different technologies for heating and cooling production while minimizing usage and investment costs. In this section, various simulations will be conducted to analyse how investments vary to meet the energy demand simulated by different software tools.
This thesis focuses on the development and assessment of the energy model for the Unterhaching district using EUReCA and UrbanHeatPro. These models have been respectively developed by the Department of Industrial Engineering at the University of Padua and by the Chair of Renewable and Sustainable Energy Systems at the Technical University of Munich (TUM). The main purpose is to analyse the differences between the two software tools and how they provide heating and cooling energy demands by simulating the behavior of an entire city, specifically Unterhaching. Consequently, two main simulations will be presented: the first simulation considers consumption using real input data from UrbanHeatPro and EUReCA as set by their respective universities (this simulation will be referred to as "simulation with no adaptation of input data"); the second simulation ("simulation with adaptation of input data") involves making the input data between the two software tools as similar as possible in order to understand whether the differences between the models stem from input data or the different models used. Subsequently, another section will be addressed where optimization will be discussed. This involves evaluating two different technologies for heating and cooling production while minimizing usage and investment costs. In this section, various simulations will be conducted to analyse how investments vary to meet the energy demand simulated by different software tools.
Development and assessment of the Unterhaching district energy model using EUReCA and Urban Heat Pro
VANZETTO, MARCO
2022/2023
Abstract
This thesis focuses on the development and assessment of the energy model for the Unterhaching district using EUReCA and UrbanHeatPro. These models have been respectively developed by the Department of Industrial Engineering at the University of Padua and by the Chair of Renewable and Sustainable Energy Systems at the Technical University of Munich (TUM). The main purpose is to analyse the differences between the two software tools and how they provide heating and cooling energy demands by simulating the behavior of an entire city, specifically Unterhaching. Consequently, two main simulations will be presented: the first simulation considers consumption using real input data from UrbanHeatPro and EUReCA as set by their respective universities (this simulation will be referred to as "simulation with no adaptation of input data"); the second simulation ("simulation with adaptation of input data") involves making the input data between the two software tools as similar as possible in order to understand whether the differences between the models stem from input data or the different models used. Subsequently, another section will be addressed where optimization will be discussed. This involves evaluating two different technologies for heating and cooling production while minimizing usage and investment costs. In this section, various simulations will be conducted to analyse how investments vary to meet the energy demand simulated by different software tools.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/60414